ArticleFrontiers in physiology2019
Deep Learning-Based Structure-Activity Relationship Modeling for Multi-Category Toxicity Classification: A Case Study of 10K Tox21 Chemicals With High-Throughput Cell-Based Androgen Receptor Bioassay Data.
Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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Who cites it
21 citing papers in PubMed.
- Semantic knowledge improves molecular machine learning for chemical toxicity prediction.iScience · 2026Article
- Tox21mer, A transformer foundation model for Tox21 high-throughput concentration-response curves data.bioRxiv : the preprint server for biology · 2026Article
- Molecular networking, conformal predictions and revised fingerprint-based models for discovering endocrine disruptors in mixtures.Analytical and bioanalytical chemistry · 2026Article
- Novel target identification towards drug repurposing based on biological activity profiles.PloS one · 2025Article
- Recent Advances in Omics, Computational Models, and Advanced Screening Methods for Drug Safety and Efficacy.Toxics · 2024Review
- Knowledge graph aids comprehensive explanation of drug and chemical toxicity.CPT: pharmacometrics & systems pharmacology · 2023Article
- DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists.Journal of cheminformatics · 2023Article
- Accurate clinical toxicity prediction using multi-task deep neural nets and contrastive molecular explanations.Scientific reports · 2023Article
- Knowledge-guided deep learning models of drug toxicity improve interpretation.Patterns (New York, N.Y.) · 2022Article
- Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries.Molecular diversity · 2022Review
- Article
- Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology.PLoS computational biology · 2021Article
- GGL-Tox: Geometric Graph Learning for Toxicity Prediction.Journal of chemical information and modeling · 2021Article
- Effect of Dataset Size and Train/Test Split Ratios in QSAR/QSPR Multiclass Classification.Molecules (Basel, Switzerland) · 2021Article
- Comparison of Machine Learning Models for the Androgen Receptor.Environmental science & technology · 2020Article
- Structure-activity relationship-based chemical classification of highly imbalanced Tox21 datasets.Journal of cheminformatics · 2020Article
- Neural network activation similarity: a new measure to assist decision making in chemical toxicology.Chemical science · 2020Article
- Molecular Image-Based Prediction Models of Nuclear Receptor Agonists and Antagonists Using the DeepSnap-Deep Learning Approach with the Tox21 10K Library.Molecules (Basel, Switzerland) · 2020Article
- KnowTox: pipeline and case study for confident prediction of potential toxic effects of compounds in early phases of development.Journal of cheminformatics · 2020Article
- Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.PloS one · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep learning (DL) has attracted the attention of computational toxicologists as it offers a potentially greater power for
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Registered trials
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